Evaluation of Targeted Systems Thinking and Systems Engineering Assessments in a Freshmen-Level Mechanical Engineering Course
- Conference
- Location
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Virtual Conference
- Publication Date
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July 26, 2021
- Start Date
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July 26, 2021
- End Date
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July 19, 2022
- Conference Session
- Tagged Division
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Systems Engineering
- Page Count
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19
- DOI
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10.18260/1-2--37110
- Permanent URL
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https://peer.asee.org/37110
- Download Count
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306
Paper Authors
Cassandra M. Birrenkott
South Dakota School of Mines and Technology
orcid.org/0000-0001-6137-0820
Dr. Cassandra (Degen) Birrenkott received her B.S. degree in Metallurgical Engineering from the South Dakota School of Mines and Technology in 2007. She received her Ph.D. in Materials Science and Engineering in 2012 from the University of Illinois at Urbana-Champaign, studying mechanochemical reactions of a spiropyran mechanophore in polymeric materials under shear loading. She is currently an Assistant Professor in the Mechanical Engineering department at the South Dakota School of Mines and Technology where her research interests include novel manufacturing and characterization techniques of polymer and composite structures and the incorporation of multifunctionality by inducing desired responses to mechanical loading.
Karim Heinz Muci-Kuchler South Dakota School of Mines and Technology
Dr. Karim Muci-Küchler is a Professor of Mechanical Engineering and Director of the Experimental and Computational Mechanics Laboratory at the South Dakota School of Mines and Technology (SDSMT). Before joining SDSMT, he was an Associate Professor of Mechanical Engineering at the University of Detroit Mercy. He received his Ph.D. in Engineering Mechanics from Iowa State University in 1992. His main interest areas include Computational Mechanics, Solid Mechanics, and Product Design and Development. He has taught several different courses at the undergraduate and graduate level, has over 50 publications, is co-author of one book, and has done consulting for industry in Mexico and the US. He can be reached at Karim.Muci@sdsmt.edu.
Mark David Bedillion
Carnegie Mellon University
orcid.org/0000-0001-5065-4131
Dr. Bedillion received the BS degree in 1998, the MS degree in 2001, and the PhD degree in 2005, all from the mechanical engineering department of Carnegie Mellon University. After a seven year career in the hard disk drive industry, Dr. Bedillion was on the faculty of the South Dakota School of Mines and Technology for over 5 years before joining Carnegie Mellon as a Teaching Faculty in 2016. Dr. Bedillion's research interests include distributed manipulation, control applications in data storage, control applications in manufacturing, and STEM education.
Marsha Lovett Carnegie Mellon University
Dr. Marsha Lovett is Associate Vice Provost of Teaching Innovation, Director of the Eberly Center for Teaching Excellence and Educational Innovation, and Teaching Professor of Psychology -- all at Carnegie Mellon University. She applies theoretical and empirical principles from learning science research to improve teaching and learning. She has published more than fifty articles in this area, co-authored the book How Learning Works: 7 Research-Based Principles for Smart Teaching, and developed several innovative, educational technologies, including StatTutor and the Learning Dashboard.
Laura Ochs Pottmeyer Carnegie Mellon University
Laura Pottmeyer is a Data Science Research Associate at Carnegie Mellon University's Eberly Center for Teaching Excellence and Educational Innovation. She consults with faculty members and graduate students on implementing educational research projects. She assists with study design, data collection, and data analysis. Laura’s training includes a Ph.D. in Science Education and M.Ed. in Educational Psychology from the University of Virginia, where she studied the impact of engineering design integrated science on student learning.
Abstract
Developing high performing, cutting edge products and systems requires engineers that, in addition to being proficient in their specific discipline, have a solid background in product development, systems engineering (SE), and systems thinking (ST). Introducing ST/SE skills gradually throughout a traditional engineering curriculum has the potential to produce graduates ready to participate in multidisciplinary teams working to develop complex products or systems. To explore how to progressively develop the ST and SE skills of mechanical engineering students, a freshman-level introduction to mechanical engineering course was utilized to incorporate basic ST/SE concepts and evaluate the gains in the knowledge, skills, and abilities (KSAs) of students in these areas.
Educational materials in the form of lectures, homework assignments, and a short project specific to freshman-level appropriate ST/SE topics were developed and implemented in an introduction to mechanical engineering course during both the Fall of 2019 and the Fall of 2020. Sample student work and scores were collected for one traditional and six newly developed homework assignments containing ST/SE questions. Rubrics for the targeted homework assignments were developed to effectively compare student work across 3 different semesters: Fall 2018 (a control group, no ST/SE intervention materials presented), Fall 2019 (first implementation of ST/SE materials), and Fall 2020 (second implementation of ST/SE materials). In this paper, the rubric development process and analysis technique will be described. In addition, the analysis of students’ KSAs in the selected ST/SE topics is used to highlight the impact of the newly implemented educational materials on students’ ST/SE understanding. Finally, the analysis is used to suggest improvement of the materials for future implementations.
Birrenkott, C. M., & Muci-Kuchler, K. H., & Bedillion, M. D., & Lovett, M., & Pottmeyer, L. O. (2021, July), Evaluation of Targeted Systems Thinking and Systems Engineering Assessments in a Freshmen-Level Mechanical Engineering Course Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37110
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